Cognitive Data Descriptors

ABSTRACT

An embodiment of the invention includes a method of managing data items based on context, where markers are associated with the data items, where the markers indicate states of authors of the data items when the data items were created. The markers can be associated with the data items by a processor. A query for a data item can be received from a user via an interface, where the query can include one or more markers indicative of the state of an author of the data item when the data item was created. The results of the query can be displayed, where the results of the query can include data items that are associated with the marker(s).

TECHNICAL FIELD

The present invention relates to systems, methods, and computer programproducts for cognitive data descriptors.

SUMMARY OF THE INVENTION

An embodiment of the invention provides a method of managing data itemsbased on context, where a processor associates markers with the dataitems. The markers can indicate one or more bodily states of the authorsof the data items when the data items were being accessed by theauthors. The bodily states of the authors can include locations of theauthor's bodies when the data items were being accessed by the author.The markers can be automatically associated with the data items withoutinput from the author indicating the bodily state of the author. A queryfor a data item can be received from a user via an interface, where thequery can include one or more markers indicative of the bodily state ofthe author of the data item when the data item was being accessed by theauthor. Results of the query can be displayed and can include data itemsthat are associated with the marker.

An embodiment of the invention provides a method including receiving aquery for a file classification from a user to be found in a filecollection; searching the file collection in response to the receivedquery; assembling the search results to the user where the searchresults include a list of files each having at least one markerincluding at least one state of at least one individual associated withthe respective file and/or at least one item of metadata; analyzing theat least one marker for at least a largest variance in the at least onemarker; applying the at least largest variance against the searchresults to locate at least two categories of files within the searchresults; and determining at least one commonality shared within eachcategory of files.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

The present invention is described with reference to the accompanyingdrawings. In the drawings, like reference numbers indicate identical orfunctionally similar elements.

FIG. 1 is a flow diagram illustrating a method for cognitive datadescriptors according to an embodiment of the invention.

FIG. 2 illustrates a graphical user interface according to an embodimentof the invention.

FIG. 3 illustrates a graphical user interface according to anotherembodiment of the invention.

FIG. 4 illustrates a list of files including a marker according to anembodiment of the invention.

FIG. 5 illustrates a list of files including cognition/mood markersaccording to an embodiment of the invention.

FIG. 6 illustrates a system for cognitive data descriptors according toan embodiment of the invention.

FIG. 7 is a flow diagram illustrating a method for cognitive datadescriptors according to an embodiment of the invention.

FIG. 8 is a diagram illustrating a computer program product forcognitive data descriptors according to an embodiment of the invention.

DETAILED DESCRIPTION

Exemplary, non-limiting, embodiments of the present invention arediscussed in detail below. While specific configurations are discussedto provide a clear understanding, it should be understood that thedisclosed configurations are provided for illustration purposes only. Aperson of ordinary skill in the art will recognize that otherconfigurations may be used without departing from the spirit and scopeof the invention.

Today, data is typically generated and stored in a file system using afixed set of descriptors of the data, which can include, for example,the file name, the time of creation, the size of the file, and/or thefile extension/type. Searching allows an individual to sort and finddata items based on these descriptors, as well as look into the data forspecific text.

At least one embodiment of the invention provides a system that usescognitive and contextual data items for file system storage, analysis,querying, and searching to allow an individual using natural languagequeries and an intuitive interface to find and analyze data itemscreated by the individual. These additional dimensions of filedescriptor association can include GPS coordinates, physical activities(e.g., accelerometry, physiological signals), and/or cognitiveassessment and state categories (e.g., arousal level, agitation, focusof attention, etc.). This can allow a search for data items to beconducted not only based on file contents, but the personal context inwhich the file was created. Also, individuals can learn about how thecontext influences the qualities of the data created, such thatoptimization of work and productivity can become possible.

The system can add files descriptors (also referred to herein as“markers”) to data items created by an individual which encapsulates thestate of the individual at the moment of creation. Specifically, thisstate can include cognitive states, physiological states, body posture,and physical location information. In addition, a history of each ofthese measures can be included in the file descriptor annotation.

FIG. 1 is a flow diagram illustrating a method for cognitive datadescriptors according to an embodiment of the invention. Cognitive,physiological, bodily, and/or physical location information can bestored in an operating system (OS) file descriptor table 110. This tablecan make use of cloud storage and block chain. When data is created by auser of the OS, a data item descriptor can be extracted from thedescriptor table, comprising specifics about the current context of datacreation, as well as a historical context 120.

An individual can compose a query on these data item descriptors whichmay include any or all of the following: any combination of the specificcontextual descriptors collected at the time of data item creation; adescription of the linear historical progression of contexts leading upto the data item creation; and a description of the topological featuresassociated with the historical progression leading up to the data itemcreation 130. The features may include number of steps, speed oftraversal, dwell times, loopiness, etc.

The system can search the data item descriptors associated with eachfile in order to provide search results 140. The user can assign arating to the returned data items in order to assess the assignments tothe historical progression via a retrospective quality assessment basedon the data produced 150. The associations of the markers to the dataitems can be updated based on the ratings by the user.

Many of the approaches described herein can facilitate the finding ofdocuments and data files, among other benefits. The challenge of findingfiles is a process that can be quite time consuming. In fact, there aretimes that users simply “give up” before finding a file from the past.Files may be created in many ways. They may be created by users usingoffice productivity tools. They may be created by programs used by users(e.g. scientific tools), and so forth. Files may be created on phones,tablets, laptops, desktop computers, and servers.

In addition to the aforementioned features, data associated with files(or segments of files) may include the kind of location when the filewas created or edited (e.g., coffee shop, airport lounge, home office,work office), etc. In fact, users may recall that they composed thedocument in a coffee shop and use recollection to help find documents.This is a cognitive aid for file finding and reminiscing about files.Data associated with files (or segments of files) may include weatherand ambient conditions (e.g., a user may remember that he was writing aportion of a document while in City X on a very warm day), device type,ambient light, and/or type of keyboard (e.g., virtual glass keyboard,physical keyboard, or voice dictation).

Furthermore, data associated with files (or segments of files) mayinclude distraction level (e.g., the user was toggling among 5 differentwindows during a half hour period while composing paragraph 27, andpicked up his phone once during this period). Metadata associated withmultiple authors who worked on the document may be included in the dataassociated with files (or segments of files). For example, Cliff was incoffee shop when composing paragraph 5, and James was at his work officewhen composing paragraph 20.

The system can include a graphical user interface (GUI) for users sothat they may weigh different parameters for searching. For example, auser is searching for a file she created about 2 years ago, and sherecalls that she was nervous and in coffee shop ABC for about 40% of thetime the document was composed. She may wish to place slightly moreweight, during her search, on the location information then the moodinformation.

FIG. 2 illustrates a GUI that is used for searching according to anembodiment of the invention. During a search, the user may wish to weigh“location” strongly, because he recalls being in his home office whilecomposing or creating a file. Although the term “editing” is used inthis GUI drawing, it can also simply refer to file creation using manydifferent methods and tools. Mood and cognition, as mentioned, can referto such aspect as distraction level, feeling tired while editing (andperhaps even having a slower typing speed because of this), and soforth. Some of this information may be specified by a user at the timethe document was being composed. For example, if a user is rushing tocomplete a paper for his boss and he is nervous, he may indicate this(e.g., with a button, via voice, etc.) to facilitate later searchers forthe file. Although FIG. 2 illustrates a dial (or knob) 210 as theinterface, other virtual items may be used instead such as a slideinterfaces 310, 320 illustrated in FIG. 3, a set of radio buttons toselect the weighting or a menu list from which the weighting may beselected.

FIG. 3 illustrates a graphical user interface according to an embodimentof the invention, where the values on the slide bar refer to an“average” for the entire data file, a median, a mode, a range, avariance, etc. For example, different parts of a file (e.g., sentences,sections, chapters, or subroutines in software) may be written atdifferent times, in different places, and in different moods by one ormore users. Thus, users may request to find a document that was “mostlycomposed” in a coffee shop, or a document for which the introduction wascomposed in a hurry. Although FIG. 3 illustrates a pair of slideinterfaces 310, 320, other interfaces may be used in place of the slideinterfaces such as the dial possibilities discussed in connection withFIG. 2.

The returned set of possible target documents or data files may besorted in order of many of the parameters mentioned above. For example,all documents composed in coffee shops or on the beach for “most” oftheir creation time may appear at the top of the search, and so forth.

During the file search, files and/or folders may bear certain easy tounderstand markers. For example, as illustrated in FIG. 4, a symbol fora coffee shop with “Wifi available” is positioned next to a foldertitled “infoquest.” This may mean, for example, that this folder wascreated while in a coffee shop, or that the majority of files within thefolder were created in a coffee shop. Similarly, individual files mayhave markings for location, emotion, mood, distraction level, typingspeed and typing error rate, etc.

FIG. 5 illustrates a list of files including cognition/mood markersaccording to an embodiment of the invention, where color and/or size ofthe marker can also play a role. Icons may be canned icons provided by aservice or tool, or defined or modified by the user. Icons may be addedautomatically (algorithmically) and/or may be added by users who wish toplay a role in “telling” the system how they feel. For example, asillustrated in FIG. 5, a user can label the “blogger” folder with anangry marker and the “cdp” folder with a sad marker. The size differencebetween the markers can indicate that the angry marker is a strongeremotion.

The frame of the GUI for an application (e.g., a word processor) maydisplay markers indicating moods, locations, etc. corresponding toparagraphs, sections, etc. of a document or data file. For example, ifparagraph 7 in a document was created with low distraction on a beach, abeach umbrella may appear to the side of the document in theapplication. A document or data file may be “sorted” by theaforementioned characteristics. For example, chapters or paragraphs maybe temporarily sorted based on location of composition, mood, cognitivefeatures, etc.

Modules may be offered to help make correlations between the type andquality of text typed into documents and the various aforementionedvariables relating to setting and cognitive state. As just one example,the Gunning fog index (readability test for English writing) may becomputed on documents, or portions of documents, and such correlationsmade.

Similarly, the Dale/Chall readability formula may be computed:

$0.4\left\lbrack {\left( \frac{words}{sentences} \right) + {100\left( \frac{{complex}\mspace{14mu} {words}}{words} \right)}} \right\rbrack$

In another embodiment, the Flesch/Kincaid readability test may becomputed:

$206.835 - {1.015\left( \frac{{total}\mspace{14mu} {words}}{{total}\mspace{14mu} {sentences}} \right)} - {84.6\left( \frac{{total}\mspace{14mu} {syllables}}{{total}\mspace{14mu} {words}} \right)}$

Various kinds of errors (and unfixed errors) in text input may bemonitored.

The term “document” may refer to emails, instant messages, technicalpapers composed in a word processor, drawing files, etc. Visual artistsmay also benefit with files like TIF, JPG, PDF, AI, MPEG, MPG, BMP,Photoshop files, and updated versions of these file types, and the like,and being able to search for them or better understand their creativityin different settings, mindsets, ambient conditions, moods, and thelike.

If a file is associated with something for sale (e.g., an artwork, abook, a paper, a technical drawing, a design, a piece of software,etc.), then metadata related to this sale may be added to the file(e.g., income derived from work, sale price, time needed to find abuyer, etc.). If a funding platform is associated with the file, folder,or platform for creative projects (e.g., one or more files associatedwith a film, music, art, theater, games, comics, design, photography,etc.), then metadata related to the funding platform may be appended(e.g., funding level, pledges of support, etc.). Cognitive and locationfeatures may also be used to mark such items.

The system can allow an individual to find data items created underconditions which are more memorable than the data items themselves.Moreover, the system can allow an individual to perform reversecorrelation on specific data items and their qualities and thehistorical contexts and features that led up to the creation of thesedata items. The system can allow an individual to optimize the creationof new data based on returning to context which were conducive to highquality data creation. In at least one embodiment, the system includesan OS file descriptor table which aggregates cognitive states,physiological states, body posture, and/or physical location informationfor the purpose of creating data items from a user of the OS, which whena file is created, provides additional features and file descriptors forstorage and association with the file. A file search interface of thesystem can be used to compose queries based on natural languagedescriptions of contexts under which a file was created. The system caninclude a historical feature association mechanism for associating afile with a feature of the traversal of context that led to the creationof the file, with the ability to query, search, and perform reversecorrelation on the files based on the historical features. Anoptimization method can be provided for recommending contexts andtraversals associated with higher quality data creation by the user. Thesystem also includes a GUI in which files or folders can be marked basedon the descriptors.

In at least one embodiment, the system allows for an additional methodof using context to gain additional insight into a file collection to beperformed. The system includes a set of files that include a variety offile types, such as document files, multimedia files, presentationfiles, drawing files, photographic files, music files etc. Each of thefiles has at least one marker associated with the file regarding the atleast one state of the at least one individual associated with the file,such as author, subject of the file, editor or reviewer, etc. and/or atleast one piece of metadata that in at least one embodiment will includehistorical markers such as time, date, and location. In at least oneembodiment, the at least one state includes at least one bodily state.In at least one embodiment, each file will have a classification of thefile that has been assigned by at least one individual where an exampleis a document code used in a document management system where the codedescribes the purpose or document type such as correspondence, courtfiling, office procedures, administrative, personal, vacation, research,great idea, etc. In a further embodiment, one or more files may havemultiple classifications assigned to them.

The method begins with receiving a query for a file classification froma user to be found in the file collection. An example of this is alldocuments classified as being associated with an invention disclosure.This query is used to search the file collection to provide an assemblyof search results to the user. In at least one embodiment, the searchresults include a list of files. Each listed or identified file hasassociated with it at least one marker.

The at least one state of at least one individual associated with therespective files and the at least one piece of metadata are analyzed forthe state or the piece of metadata that provides the largest variance inthe at least one marker. For example, the search results for theinvention disclosure files provides a variance in states associated withthe individual's heart rate. In a further embodiment, multiple variancesare determined and used in later steps to learn additional informationregarding the files.

The located variance is then applied to the search results to see ifthere are any categories such as at least two categories of files thatshare the variance(s) for at least one marker within the search results.For example, the individual's heart rate variance where it is elevatedfor at least one hour as to being the normal heart rate for theindividual is used to divide the invention disclosure files into twocategories. Variance is only one such statistic that may be applied tohistorical recordings of data such as heart rate.

Each category of files is analyzed to determine whether there is ashared aspect or commonality internal to each category of files. Forexample, invention disclosures rated to be filed were associated withone heart rate while invention disclosures rated to not be file wereassociated with the other heart rate. This analysis may be performed byexamining each state and/or type of metadata for the files in eachcategory looking for something shared between all of the files where thestate and/or type of metadata is the same or similar to each other. In afurther embodiment, these correlations and statistics may provideinsight to the user of different ways to search for similar fileclassifications to locate a relevant document. In a further embodiment,the at least one commonality is added as at least one state for eachrespective file.

In at least one embodiment, the method allows for the identification ofunrelated criteria to identify new information about the conditions inwhich the file and/or data associated with the file was created.

FIG. 6 illustrates a system 600 for managing data items (also referredto herein as “files” or “documents”) based on context according to anembodiment of the invention, wherein the system 600 includes a processor610, an interface 620, and a display 630. FIG. 7 is a flow diagramillustrating a method of managing data items based on context accordingto an embodiment of the invention (e.g., using the system 600).

The processor 610 can identify the state of an author of a data item(710). The state of the author can be identified from manual input fromthe author via an interface and/or from one or more sensors on orproximate to the author.

The state of the author can include GPS coordinates, a city, a streetaddress, a name of a business, and/or a name selected by a user. In atleast one embodiment, the state of the author includes one or more moodsof the author (e.g., happy, sad, frustrated, angry, bored, anxious,nervous, sleepy, fatigued, excited, etc.), one or more physiologicalstates of the author (e.g., body temperature, posture, limbconfiguration, muscle tone, muscle movement, respiration rate, measuresof digestion, skin conductance, facial expression, EEG, EMG, pupildilation, spasticity, spasmodicity, and/or heartrate), weatherexperienced by the author (e.g., sunny, rainy, cloudy, partly cloudy,drizzle, hurricane, snowing, blizzard, etc.), the device type used bythe author when the data item was accessed (smart phone, smart watch,smart camera, tablet computer, home computer, work computer, publiccomputer, hotel computer, library computer, etc.), and/or the level ofdistraction of the author (e.g., distracted, not distracted, moderatelydistracted, score from 1-10, etc.).

The processor 610 can associate markers with the data items (720), wherethe markers can indicate states of the authors of the data items whenthe data items were being accessed by the authors. As used herein, theterm “accessed” includes created, edited, revised, modified, and viewed.The association of the markers with the data items can be based on inputmanually entered into the interface by the authors. For example, anauthor of a word processing document can tag the document with a markerusing a mouse and a drop-down menu, where the marker indicates that thedocument was revised at the law library at the state university. Inanother embodiment, the association of the markers with the data itemsis automatically performed by the processor 610 without input from theauthors indicating the states of the authors. For example, when anauthor of a photograph creates the photograph, the processor 610automatically associates a marker with the photograph without input fromthe author indicating the state of the author, where the markerindicates that the photograph was created when the author was angry.

In at least one embodiment, a query for a data item is received from auser (e.g., the author) via the interface 620 (730), where the queryincludes at least one marker indicative of a state of an author of thedata item when the data item was being accessed by the author. As usedherein, the term “interface” includes a computer hardware device, suchas, for example, a keyboard, a mouse, a microphone, a touchpad, atouchscreen, a joystick, a controller, a camera, a disk drive, an inputport, an output port, an antenna, etc. For example, the user issearching for an inventory spreadsheet that she modified when she wasangry, so she submits the query “inventory spreadsheet angry” via akeyboard.

The query can include weighted coefficient(s) for the marker(s). Forexample, an author thinks that he was a little sleepy, moderatelynervous, and very frustrated when he created a file, so his queryincludes the weighted coefficients 0.5, 1.0, and 1.5 for the markerssleepy, nervous, and frustrated, respectively.

In at least one embodiment, the processor 610 associates a historicalprogression of author states with the data item(s), and the queryincludes the historical progression of author states. For example, theauthor remembers that she was initially frustrated when she was editinga document, then she felt sad that she had to miss a party, then shefelt happy that she accomplished a goal. The author can include thehistorical progression marker frustrated-sad-happy in her query.

The results of the query can be displayed on the display 630 (740),where the results of the query include data items that are associatedwith the marker(s) in the query. As used herein, the term “display”includes a computer hardware device, such as, for example, a monitor ortouch screen. The user can enter a rating of one or more search resultsvia the interface 620, where the rating can indicate a retrospectiveaccuracy assessment of the association of the marker with the searchresult. For example, if a search result is exactly what the user waslooking for, he can rate the search result as a 5. If, however, thesearch result is far from what the user was looking for (e.g., thesearch result is a photograph created when he was happy when the userwas looking for a document he reviewed when he was angry), he can ratethe search result as a 0.

The present invention may be a system, a method, and/or a computerprogram product at any possible technical detail level of integration.The computer program product may include a computer readable storagemedium (or media) having computer readable program instructions thereonfor causing a processor to carry out aspects of the present invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, configuration data for integrated circuitry, oreither source code or object code written in any combination of one ormore programming languages, including an object oriented programminglanguage such as Smalltalk, C++, or the like, and procedural programminglanguages, such as the “C” programming language or similar programminglanguages. The computer readable program instructions may executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or entirely on the remote computer or server. Inthe latter scenario, the remote computer may be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection may be made to anexternal computer (for example, through the Internet using an InternetService Provider). In some embodiments, electronic circuitry including,for example, programmable logic circuitry, field-programmable gatearrays (FPGA), or programmable logic arrays (PLA) may execute thecomputer readable program instructions by utilizing state information ofthe computer readable program instructions to personalize the electroniccircuitry, in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the blocks may occur out of theorder noted in the Figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

Referring now to FIG. 8, a representative hardware environment forpracticing at least one embodiment of the invention is depicted. Thisschematic drawing illustrates a hardware configuration of an informationhandling/computer system in accordance with at least one embodiment ofthe invention. The system comprises at least one processor or centralprocessing unit (CPU) 10. The CPUs 10 are interconnected with system bus12 to various devices such as a random access memory (RAM) 14, read-onlymemory (ROM) 16, and an input/output (I/O) adapter 18. The I/O adapter18 can connect to peripheral devices, such as disk units 11 and tapedrives 13, or other program storage devices that are readable by thesystem. The system can read the inventive instructions on the programstorage devices and follow these instructions to execute the methodologyof at least one embodiment of the invention. The system further includesa user interface adapter 19 that connects a keyboard 15, mouse 17,speaker 24, microphone 22, and/or other user interface devices such as atouch screen device (not shown) to the bus 12 to gather user input.Additionally, a communication adapter 20 connects the bus 12 to a dataprocessing network 25, and a display adapter 21 connects the bus 12 to adisplay device 23 which may be embodied as an output device such as amonitor, printer, or transmitter, for example.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the invention. Asused herein, the singular forms “a”, “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the root terms “include”and/or “have”, when used in this specification, specify the presence ofstated features, integers, steps, operations, elements, and/orcomponents, but do not preclude the presence or addition of at least oneother feature, integer, step, operation, element, component, and/orgroups thereof.

The corresponding structures, materials, acts, and equivalents of allmeans plus function elements in the claims below are intended to includeany structure, or material, for performing the function in combinationwith other claimed elements as specifically claimed. The description ofthe present invention has been presented for purposes of illustrationand description, but is not intended to be exhaustive or limited to theinvention in the form disclosed. Many modifications and variations willbe apparent to those of ordinary skill in the art without departing fromthe scope and spirit of the invention. The embodiment was chosen anddescribed in order to best explain the principles of the invention andthe practical application, and to enable others of ordinary skill in theart to understand the invention for various embodiments with variousmodifications as are suited to the particular use contemplated.

What is claimed is:
 1. A method of managing data items based on context,said method comprising: associating markers with the data items, themarkers indicating states of at least one author of the data items whenthe data items were being accessed by the at least one author, themarkers being associated with the data items by a processor; receiving aquery for a data item from a user via an interface, the query includingat least one marker indicative of a state of an author of the data itemwhen the data item was being accessed by the author; and displayingresults of the query, the results of the query including data items thatare associated with the at least one marker.
 2. The method according toclaim 1, wherein said associating of the markers with the data items isbased on input manually entered into the interface by the at least oneauthor.
 3. The method according to claim 1, wherein said associating ofthe markers with the data items is automatically performed by theprocessor without input from the at least one author indicating thestates of the at least one author.
 4. The method according to claim 1,wherein the state of the at least one author is selected from a groupconsisting of GPS coordinates, a city, a street address, a name of abusiness, and a name selected by the user.
 5. The method according toclaim 1, wherein the state of the author includes a mood of the author.6. The method according to claim 1, wherein the state of the authorincludes a physiological state of the author.
 7. The method according toclaim 6, wherein the physiological state of the author is selected fromthe group consisting of body temperature, posture, limb configuration,muscle tone, muscle movement, respiration rate, measures of digestion,skin conductance, facial expression, EEG, EMG, pupil dilation,spasticity, spasmodicity, and heartrate.
 8. The method according toclaim 1, wherein the state of the author includes weather experienced bythe author.
 9. The method according to claim 1, wherein the state of theauthor includes a device type used by the author when the data item wasaccessed.
 10. The method according to claim 1, wherein the state of theauthor includes a level of distraction.
 11. The method according toclaim 1, wherein said associating of the markers with the data itemsincludes associating a historical progression of author states with atleast one of the data items, and wherein the query includes thehistorical progression of author states.
 12. The method according toclaim 1, further including receiving a rating of a search result fromthe user, the rating indicating a retrospective accuracy assessment ofthe association of the marker with the search result.
 13. The methodaccording to claim 1, wherein the query includes at least one weightedcoefficient for the at least one marker indicative of the state of theat least one author of the data item when the data item was accessed.14. The method according to claim 1, further comprising receiving arating from the user of at least one of the results of the query,wherein the rating indicating a retrospective accuracy assessment of theassociation of the marker with the at least one results of the query.15. The method according to claim 1, wherein the at least one state isat least one bodily state, the at least one bodily state of the at leastone author including locations of the at least one author's bodies whenthe data items were being accessed by the at least one author, themarkers being automatically associated with the data items by aprocessor without input from the at least one author indicating the atleast one bodily state of the at least one author.
 16. The methodaccording to claim 15, wherein the at least one bodily state of the atleast one author is selected from a group consisting of GPS coordinates,a city, a street address, a name of a business, and a name of the bodilystate selected by a user; or the at least one bodily state of the atleast one author includes a mood of the author; or the at least onebodily state of the at least one author is selected from the groupconsisting of body temperature, posture, limb configuration, muscletone, muscle movement, respiration rate, measures of digestion, skinconductance, facial expression, EEG, EMG, pupil dilation, spasticity,spasmodicity, and heartrate; or the at least one bodily state of the atleast one author is selected from the group consisting of weatherexperienced by the author, a device type used by the author, and a levelof distraction.
 17. The method according to claim 15, wherein saidassociating of the markers with the data items includes associating ahistorical progression of author bodily states with at least one of thedata items, and wherein said query includes the historical progressionof author bodily states.
 18. A method comprising: receiving a query fora file classification from a user to be found in a file collection;searching the file collection in response to the received query;assembling the search results to the user where the search resultsinclude a list of files each having at least one marker including atleast one state of at least one individual associated with therespective file and/or at least one item of metadata; analyzing the atleast one marker for at least a largest variance in the at least onemarker; applying the at least largest variance against the searchresults to locate at least two categories of files within the searchresults; and determining at least one commonality shared within eachcategory of files.
 19. The method according to claim 18, furthercomprising adding the at least one commonality as a new state for eachrespective file; and wherein the metadata includes historical markersand the file classification includes how the file was classified by atleast one individual associated with the respective file.
 20. A computerprogram product for managing data items, said computer program productcomprising: a computer readable storage medium having stored thereon:first program instructions executable by a device to cause the device toassociate markers with the data items, the markers indicating bodilystates of at least one author of the data items when the data items werebeing accessed by at least one author; second program instructionsexecutable by the device to cause the device to receive a query for adata item from a user, the query including at least one markerindicative of a state of an author of the data item when the data itemwas being accessed by the at least one author; and third programinstructions executable by the device to cause the device to displayresults of the query, the results of the query including data items thatare associated with the at least one marker.